Book of Extended summaries ISDA

International Conference on Reimagining Rainfed Agro-ecosystems: Challenges &
Opportunities during 22-24, December 2022 at ICAR-CRIDA, Hyderabad
T3-42P
Assessment of Genetic Diversity among the Maize (Zea mays L.) Genotypes
Based on SSR Markers Linked to Drought Tolerance
P. Sathish*, M. Vanaja, Y. Varalaxmi, B. Sarkar, N. Jyothi Lakshmi, S.K. Yadav, Ch.
Mohan, A. Sushma and M. Prabhakar
ICAR - Central Research Institute for Dryland Agriculture, Hyderabad-500 059, India
*p.sathish2@icar.gov.in
Maize (Zea mays L.) is the third most important cereal crop after wheat and rice in terms of
global grain production. Drought is one of the most important abiotic stresses limiting crop
yield by 15, 40%, and 60% at vegetative, pollination and grain filling periods respectively.
Diversity among maize germplasm is important for identifying parental lines for successful
breeding programme and development of hybrids with adaptation to a broad range of
environments. Among the different types of molecular markers, simple sequence repeats
(SSRs) are one of the most promising molecular markers and quite useful in assessment of
genetic diversity, marker assisted selection and genetic studies such as construction of linkage
maps and QTL mapping. The present study was aimed to identify diverse genotypes of maize
for genetic enhancement of drought tolerance.
Methodology
Twelve maize genotypes were obtained from different sources viz., ICAR-IIMR, New Delhi;
ICAR-NBPGR, Hyderabad; ICAR-CRIDA; Maize Research Centre, PJTSAU, Hyderabad.
The crop was sown during kharif 2021 at ICAR- CRIDA, Hyderabad, to assess the genetic
diversity among the genotypes. The recommended fertilizer dose and cultural practices along
with plant protection measures were followed to raise the crop. Each genotype genomic DNA
was extracted from young leaves at 3- to 4-week-old plants following CTAB method (Doyle
and Doyle, 1990) with slight modifications. Genomic SSR markers (25) reported having
association with drought tolerance traits belonging to different series viz., bnlg, umc, and phi
were selected. These markers were selected based on their repeat units and bin location to
provide uniform coverage of entire maize genome. The SSR amplification of gel images and
marker data were processed using Biovision software, USA. The molecular weight data were
used to calculate the number of alleles, heterozygosity, and polymorphism information content
(PIC) for each of the primer pairs using Power Marker 3.25 software (Liu and Muse 2005).
The binary data of SSR markers was used for cluster analysis and the dendrogram was
generated based on similarity matrices obtained with the unweighted pair-group method using
the arithmetic mean (UPGMA). All the data analysis was carried out using the NTSYS-pc2.0
software package (Rohlf, 1998).
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